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Improvement of the chemical content prediction of a modelpowder system by reducing multiple scattering usingpolarized light spectroscopy
Ryad Bendoula, Alexia Gobrecht, Bruno Moulin, Jean-Michel Roger, Véronique Bellon Maurel

Improvement of the chemical content prediction of a modelpowder system by reducing multiple scattering usingpolarized light spectroscopy

Science & Mathematics Published 2015 Verification Pending

Overview & Synopsis

Near-infrared spectroscopy (NIRS) is a powerful non-destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in line in industries, in vivo with biomedical applications, or in field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentration. Instead of spectral pre-processing, which is commonly used by NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, i.e., coupling polarized light with NIR spectrometry, to free spectra from scattering effect. This should allow us to retrieve linear and steady conditions for spectral analysis. When tested in visible-NIR (Vis-NIR) range (400-800 nm) on model media, mixtures of scattering and absorbing particles, the setup provided significant improvements in absorber concentration estimation precision as well as in the quality and robustness of the calibration model.

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Document Information

Document Title Improvement of the chemical content prediction of a modelpowder system by reducing multiple scattering usingpolarized light spectroscopy
Author / Organization Ryad Bendoula, Alexia Gobrecht, Bruno Moulin, Jean-Michel Roger, Véronique Bellon Maurel
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2015
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-251602
Original Source Link Visit Source Page on hal.science »